基于自适应M-H采样的放射源定位算法
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摘要
针对放射源定位中的仪器设施昂贵且定位过程复杂的问题,提出了一种自适应M-H采样的放射源定位算法。利用轻便的个人剂量仪获取辐射场内不同测量点的剂量;再根据放射源的空间衰变规律,建立点放射源位置估计的贝叶斯推理模型,得到放射源参数的后验分布;通过自适应调整初始值和提议函数方差的M-H算法对后验分布进行采样,实现了室内环境中点放射源的定位。采用Eu-152展开实验,实验结果表明:提出的算法能够以较小的误差定位裸源,方法可行、有效。
In order to solve the problem of expensive instrumentation and complicated positioning process in locating radioactive sources,a self-adaptive M-H sampling algorithm for locating the radioactive sources is proposed. Firstly,the dose of different measurement points in the radiation field was obtained by a portable personal dosimeter.Then, based on the spatial decay law of the source,a Bayesian inference model for estimating the position of the point source was established, and the posterior distribution of the source parameters was obtained. Finally,the posterior distribution was sampled by the M-H algorithm which adaptively adjusts the initial value and the proposed function variance to realize the localization of the point source in the indoor environment.The experiments were carried out with Eu-152.The experimental results show that the proposed algorithm can locate the bare source with a small error,and the method is feasible and effective.
In order to solve the problem of expensive instrumentation and complicated positioning process in locating radioactive sources,a self-adaptive M-H sampling algorithm for locating the radioactive sources is proposed. Firstly,the dose of different measurement points in the radiation field was obtained by a portable personal dosimeter.Then, based on the spatial decay law of the source,a Bayesian inference model for estimating the position of the point source was established, and the posterior distribution of the source parameters was obtained. Finally,the posterior distribution was sampled by the M-H algorithm which adaptively adjusts the initial value and the proposed function variance to realize the localization of the point source in the indoor environment.The experiments were carried out with Eu-152.The experimental results show that the proposed algorithm can locate the bare source with a small error,and the method is feasible and effective.
引文
[1]国家核安全局.中华人民共和国国家核安全局2016年报[EB/OL].[2017-11-07].http://nnsa.mep.gov.cn/zhxx_8953/haqnb/201707/P020170712499760277634.pdf.
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[16]陈平,徐若曦.Metropolis Hastings自适应算法及其应用[J].系统工程理论与实践,2008,28(1):100-108.
[17] Roberts G 0,Gelman A,Gilks W R.Weak convergence and optimal scaling of random walk metropolis algorithms[J].The Annals of Applied Probability,1997,7(1):110-120.
[18] Gelman A,Carlin J B,Stern H S,et al.Bayesian Data Analysis[M].3rd ed.London:Chapman and Hall,2013.
[2] Sun S F,Zhang Z M,Shuai L,et al.Far field 3D localization of radioactive hot spots using a coded aperture camera[J].Applied Radiation and Isotopes,2016,107:177-182.
[3]张译文,章志明,李道武,等.基于多探测节点的放射源监测及定位方法研究[J].原子能科学技术,2016,50(4):705-712.
[4]左国平,谭军文,周剑良,等.基于三角圆筒铅屏蔽NaI探测器的放射源定位研究[J].原子能科学技术,2017,51(3):515-521.
[5] Miller E A,Robinson S M,Anderson K K,et al.Adaptively reevaluated Bayesian localization(ARBL):a novel technique for radiological source localization[J].Nuclear Instruments and Methods in Physics Research Section A,2015,784:332-338.
[6] Sharma M K,Alajo A B,Lee H K.Three-dimensional localization of low activity gamma-ray sources in real-time scenarios[J]. Nuclear Instruments and Methods in Physics Research A,2016,813:132-138.
[7] Pahlajani C D,Poulakakis I,Tanner H G.Networked decision making for poisson processes with applications to nuclear detection[J].IEEE Transactions on Automatic Control,2014,59(1):193-198.
[8] Bai E W,Heifetz A,Raptis P,et al.Maximum likelihood localization of radioactive sources against a highly fluctuating background[J]. IEEE Transactions on Nuclear Science,2015,62(6):3274-3282.
[9] Liu R, Zell A. On Tracking Dynamic Objects with Long Range Passive UHF RFID Using a Mobile Robot[M].Taylor&Francis,Inc.,2015.
[10] Fu Y L,Wang C L,Liu R,et al.Moving object localization based on UHF RFID phase and laser clustering[J]. Sensors,2018,18(3):825.
[11]仝兆景,时俊岭,高彩霞,等.基于贝叶斯网络的变压器在线监测与分析系统设计[J].测控技术,2018,37(2):114-117.
[12] Gunatilaka A,Ristic B,Gailis R.Radiological Source Localisation[R]. Australia:Defense Sciences and Technology Organization,2007.
[13] Ristic B,Morelande M,Gunatilaka A. Information driven search for point sources of gamma radiation[J].Signal Processing,2010,90(4):1225-1239.
[14]汤彬,葛良全,方方,等.核辐射测量原理[M].哈尔滨:哈尔滨工程大学出版社,2011.
[15] Mcdougall R. Robotic radiation mapping using modelling and probabilistic analysis of sparse data[D].Oshawa,Canada:University of Ontario Institute of Technology,2015.
[16]陈平,徐若曦.Metropolis Hastings自适应算法及其应用[J].系统工程理论与实践,2008,28(1):100-108.
[17] Roberts G 0,Gelman A,Gilks W R.Weak convergence and optimal scaling of random walk metropolis algorithms[J].The Annals of Applied Probability,1997,7(1):110-120.
[18] Gelman A,Carlin J B,Stern H S,et al.Bayesian Data Analysis[M].3rd ed.London:Chapman and Hall,2013.
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